As the digital image processing techniques continuously advance, more and more products relating to image recognition hit the market. Examples of such products include digital cameras capable of human face recognition, dashcams capable of recognizing pedestrians, and surveillance monitors capable of calculating pedestrian flow. Efforts have been made in the academic as well as industrial circles for computers to recognize digital images like human beings do.
With the convolution neural network (CNN), preferable results have been rendered in digital image recognition. The convolution neural network not only facilitates the performance of whole-image classification, but also reinforce the capability of local image recognition. Nevertheless, image recognition adopting technologies such as the convolution neural network may be affected by a shielding object covering the target, and the recognition rate is thus affected. Hence, image recognition technologies still require attention of the researchers.